Use case 01
Use it when you want to begin experimental design and methodology work without writing the first draft from scratch.
Research ScientistExperimental Design and MethodologyAdvancedChain
Full Study Design Chain AI Prompt
Step 1: Sharpen the research question — convert the broad research area into a specific, answerable, PICO-structured research question with clearly operationalized constructs an... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.
Prompt text
Step 1: Sharpen the research question — convert the broad research area into a specific, answerable, PICO-structured research question with clearly operationalized constructs and a defined unit of analysis. Step 2: Select the study design — identify the strongest feasible design given the research question and available resources. State what causal claims the chosen design can and cannot support. Step 3: Design the control condition — specify the comparison condition, what it controls for, and what it leaves uncontrolled. Design the blinding procedure. Step 4: Confound analysis — systematically identify all potential confounders by category. Specify the control strategy for each. Acknowledge what residual confounding remains. Step 5: Measurement plan — specify the operationalization of each construct. Provide psychometric evidence for each instrument. Identify measurement invariance requirements. Step 6: Validity audit — audit the design for threats to internal, construct, statistical conclusion, and external validity. Document mitigation strategies. Step 7: Pre-mortem — assume the study failed and identify the most likely causes. Modify the protocol to prevent or detect each failure mode. Step 8: Write the methods section — produce a complete methods section covering: participants (eligibility, recruitment, sample size), design, procedure, measures, and analysis plan. Write with sufficient detail for independent replication.
When to use this prompt
Use case 02
Use it when you want a more consistent structure for AI output across projects or datasets.
Use case 03
Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.
Use case 04
Use it when you want a clear next step into adjacent prompts in Experimental Design and Methodology or the wider Research Scientist library.
What the AI should return
The AI should return a structured result that is directly usable in a experimental design and methodology workflow, with explicit outputs, readable formatting, and enough clarity to support the next step in research scientist work.
How to use this prompt
1
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
2
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
3
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
4
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Experimental Design and Methodology.
Frequently asked questions
What does the Full Study Design Chain prompt do?+
It gives you a structured experimental design and methodology starting point for research scientist work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for research scientist workflows and marked as advanced, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Full Study Design Chain is a chain. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Confound Identification, Control Condition Designer, Measurement Instrument Evaluation.